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Record W4416407516 · doi:10.1002/aisy.202500745

Design of a Reconfigurable Microfluidic System Enabled by Magnetic Miniature Robots

2025· article· en· W4416407516 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvanced Intelligent Systems · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of Toronto
FundersUniversidade de MacauNational Natural Science Foundation of ChinaFundo para o Desenvolvimento das Ciências e da TecnologiaUnited Mitochondrial Disease Foundation
KeywordsMicrofluidicsScalabilityMicrochannelRobotActuatorMagnetic nanoparticlesControl reconfigurationFluidicsFlow control (data)

Abstract

fetched live from OpenAlex

Microfluidics permits fluid operations at the microscale. Conventional microfluidic devices have fixed structural configurations, which restrict their adaptability for different applications. A new approach is proposed by integrating magnetic miniature robotic systems into microfluidic platforms, thereby enabling dynamic reconfiguration of the microfluidic chip. As a demonstration, the study presents four types of magnetic miniature robots, i.e., magnetic sorting robot, magnetic variable channel robot, magnetic gyroscope robot, and magnetic rotating flow channel robot, to achieve on‐chip sorting, dynamic regulation of fluid velocity, on‐chip flow regulation, and rapid mixing and bubble manipulation. This work presents a versatile and scalable solution for reconfigurable microfluidic systems, opening new avenues for real‐time control in biological and chemical processes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.226
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it